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Sensitivity Auditing Andrea Saltelli Centre for the Study of the Sciences and the Humanities (SVT) - University of Bergen (UIB) Institut de Ciència i Tecnologia Ambientals (ICTA) - Universitat Autonoma de Barcelona (UAB) ROME, November 10-11 2015 CHALLENGES OF BIG DATA FOR ECONOMIC MODELING AND MANAGEMENT: TOOLS FROM EFFICIENCY ANALYSIS, SENSITIVITY ANALYSIS, SENSITIVITY AUDITING AND PHYSICS OF COMPLEX SYSTEMS Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG) Sapienza University of Rome, Aula Magna, Via Ariosto, 25 [email protected]

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Page 1: Andrea Saltelli

Sensitivity Auditing

Andrea Saltelli Centre for the Study of the Sciences and the

Humanities (SVT) - University of Bergen (UIB)

Institut de Ciència i Tecnologia Ambientals (ICTA) -Universitat Autonoma de Barcelona (UAB)

ROME, November 10-11 2015CHALLENGES OF BIG DATA FOR ECONOMIC MODELING

AND MANAGEMENT: TOOLS FROM EFFICIENCY ANALYSIS, SENSITIVITY ANALYSIS, SENSITIVITY AUDITING AND

PHYSICS OF COMPLEX SYSTEMSDepartment of Computer, Control and Management

Engineering Antonio Ruberti (DIAG)Sapienza University of Rome, Aula Magna, Via Ariosto, 25

[email protected]

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Topics for this course

Sensitivity Analysis

Sensitivity Auditing

Impact Assessment

Science advice

Science’s crisis

Science and Technology Studies (STS)

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Sensitivity auditing

•Originates from uncertainty & sensitivity analysis

•Addresses model-based evidence used for policy

Saltelli, A., Guimarães Pereira, Â., Van der Sluijs, J.P. and Funtowicz, S., 2013, What do I make of your latinorum?

Sensitivity auditing of mathematical modelling, Int. J. Foresight and Innovation Policy, 9, 2/3/4, 213–234.

Saltelli, A., Funtowicz, S., When all models are wrong: More stringent quality criteria are needed for models used at the

science-policy interface, Issues in Science and Technology, Winter 2014, 79-85.

http://issues.org/30-2/andrea/

Sensitivity auditing in pills:

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The instrumental use of

mathematical modelling

to advance one’s agenda

can be termed rhetorical,

or strategic, like the use

of Latin by the elites and

the clergy in the classic

age.

RULE ONE: Check against rhetorical use

of mathematical modelling

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Pocket Books 1987, p.69

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“Well, Gordon’s great insight was to design a

program which allowed you to specify in advance

what decision you wished it to reach, and only then

to give it all the facts. The program’s task, […], was

to construct a plausible series of logical-sounding

steps to connect the premises with the conclusion.”

RULE ONE: Check against rhetorical use

of mathematical modelling

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Useless Arithmetic: Why

Environmental Scientists Can't

Predict the Future

by Orrin H. Pilkey and Linda

Pilkey-Jarvis

‘Quantitative mathematical models

used by policy makers and

government administrators to form

environmental policies are seriously

flawed’

RULE ONE: Check against rhetorical use

of mathematical modelling

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The problem of legitimization – quantitative

analysis as a rhetorical or ritual device - the

story of Nobel prize laureate Kenneth Arrow:

“The commanding general is well aware that the forecasts are

no good. However, he needs them for planning

purposes”(Szenberg, 1992).

RULE ONE: Check against rhetorical use

of mathematical modelling

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What was ‘assumed out’? What are the

tacit, pre-analytic, possibly normative

assumptions underlying the analysis?

E.g. in ‘Bogus Quantification: Uses and

Abuses of Models’ John Kay

uncovers that the UK transport

WebTAG model (the standard for

transport policy simulation) needs as

input ‘Annual Percentage Change in

Car Occupancy up to 2036.’

RULE TWO: Adopt an ‘assumption hunting’ attitude;

John Kay, London

School

Economics,

Columnist

Financial Times

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John Kay’s approach is called ‘Assumptions hunting’ in

Dutch circles …

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‘[…] calculation of the external costs of a potential

large-scale nuclear accident […] ‘An [analysis] resulted

in a list of 30 calculation steps and assumptions’ …

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Who should do the hunting? Implication of Rule 2 for

participatory approaches introducing a worked example

from flood management.

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[…] knowledge regarding flooding was co-produced. This illustrates a

way of working with experts, both certified (academic natural and social

scientists) and noncertified (local people affected by flooding), […] We

reveal a deep and distributed understanding of flood hydrology across all

experts, certified and uncertified, …

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Years of modeling stream flow and cost/benefit ratios for

flood protection structures had failed to consider an

alternative intervention—upstream storage of flood

waters—until local stakeholders were brought into the

modeling process.

According to Lane and colleagues, upstream storage was

neglected in the models because of the “use of a pit-filling

algorithm that made sure that all water flows downhill”!

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RULE THREE: detect GIGO (Garbage In, Garbage Out)

Science or pseudo-science

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“where uncertainties in inputs must be suppressed lest outputs

become indeterminate”From: Uncertainty and Quality in Science for Policy

by Silvio Funtowicz and Jerry Ravetz, Springer 1990.

RULE THREE: detect GIGO (Garbage In, Garbage Out)

Science or pseudo-science

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<<I have proposed a form of organised sensitivity analysis that I

call “global sensitivity analysis” in which a neighborhood of

alternative assumptions is selected and the corresponding

interval of inferences is identified.

Conclusions are judged to be sturdy only if the neighborhood of

assumptions is wide enough to be credible and the

corresponding interval of inferences is narrow enough to be

useful.>>

Edward E. Leamer, 1990, Let's Take the Con

Out of Econometrics, American Economics

Review, 73 (March 1983), 31-43.

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RULE FOUR: find sensitivities before sensitivities find you;

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From: Saltelli, A., D'Hombres, 2010, Sensitivity

analysis didn't help. A practitioner's critique of the

Stern review, GLOBAL ENVIRONMENTAL

CHANGE, 20, 298-302.

RULE FOUR: find sensitivities before sensitivities find you;

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Nicholas Stern, London

School of Economics

The case of Stern’s Review – Technical Annex to postscript

William Nordhaus,

University of Yale

Stern, N., Stern Review on the Economics of Climate Change.

UK Government Economic Service, London,

www.sternreview.org.uk.

Nordhaus W., Critical Assumptions in the Stern Review on

Climate Change, SCIENCE, 317, 201-202, (2007).

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The Stern - Nordhaus exchange on SCIENCE

1) Nordhaus falsifies Stern based on ‘wrong’ range of

discount rate

2) Stern’s complements its review with a postscript: a

sensitivity analysis of the cost benefit analysis

3) Stern infers: My analysis shows robustness’

RULE FOUR: find sensitivities before sensitivities find you;

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My problems with it:

!

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… but foremost Stern says:

changing assumptions important effect

when instead he should admit that:

changing assumptions all changes a lot

% lo

ss in

GD

P p

er

cap

ita

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How was it done? A reverse engineering of the analysis

% loss in GDP per capita

Missing points

Large uncertainty

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Same criticism applies to Nordhaus – both authors frame the

debate around numbers which are …

… precisely wrong

RULE FOUR: find sensitivities before sensitivities find you;

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Peter Kennedy, A Guide to Econometrics.

Anticipating criticism by applying sensitivity

analysis. This is one of the ten commandments

of applied econometrics:

<<Thou shall confess in the presence of

sensitivity.

Corollary: Thou shall anticipate criticism >>

RULE FOUR: find sensitivities before sensitivities find you;

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RULE FIVE: aim for transparency

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“Experts have “raised a host of

questions” about how the

European Commission’s use of a

non-transparent model could

affect the energy review, according

to a leaked report by energy

specialists chosen by Brussels to

advise on the forthcoming

“Energy Roadmap to 2050”

FT November 6, 2011

RULE FIVE: aim for transparency

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“The credibility of a European

energy review has been cast into

doubt by experts who point out that

long-term plans to cut carbon

emissions are based on an economic

model owned by a single Greek

university that cannot be

independently scrutinised.”

RULE FIVE: aim for transparency

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The OMB about transparency

http://www.whitehouse.gov/omb/inforeg/

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[models should be made available to a third party so that it can

] use the same data, computer model or statistical methods to

replicate the analytic results reported in the original study.

[…] The more important benefit of transparency is that the

public will be able to assess how much an agency’s analytic

result hinges on the specific analytic choices made by the

agency.

Friday, February 22, 2002

Graphic - Federal Register, Part IX

Office of Management and Budget

Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, and Integrity

of Information Disseminated by Federal Agencies; Notice; Republication

http://www.whitehouse.gov/omb/inforeg/

This was 2002

RULE FIVE: aim for transparency

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This is 2014

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The bill, dubbed the Secret Science Reform Act would force

the EPA to publicly release its research on a topic before

issuing a policy recommendation, and require that the

research be "reproducible." Supporters claim the bill will

increase transparency in public policy, while opponents have

accused the

bill's authors of trying to “keep the EPA from doing its

job.”

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http://beta.congress.gov/bill/113th-congress/house-bill/4012

Accessed May 2014

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Do the sum right

Versus

Do the right sums

(Stephen Toulmin)

A plea for reasonableness

versus rationality

RULE SIX: Do the right sums

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Peter Kennedy’s commandment of applied

econometrics: ‘Thou shall answer the right

question’, Kennedy 2007

RULE SIX: Do the right sums

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Expertise and responsibility Rule 6

• Experts as stakeholders among many, with

their occupational psychoses.

• Example: most analyses offered as input to

policy are framed as cost benefit analysis

(monetization, the occupational psychosis

of economists) or risk analyses.

• Techniques (such as CBA) is never neutral;

according to Winner (1986) ecologists

should not fall into the trap of CBA.

Winner, L., 1986. The Whale and the Reactor: a Search for Limits in an Age of High Technology. The

University of Chicago Press, 1989 edition.

Langdon Winner

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Frames

• Contrary to the popular belief that climate sceptics don’t

know about climate science Dan Kahan (2014) has

observed that the more a person is informed about

climate science, the more he or she is likely to be polarized

on the issue in either direction.

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Frames

• Contrary to the popular belief that a GMO-averse

person is a risk- or technology-averse individual, an

important EC study (Marris, 2001) has shown that

GMO aversion is linked to frames where risk plays a

very minimal role (and alimentary risk plays no role at

all).

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Frames

• The expression ‘tax relief ’ is apparently innocuous but it

suggests that tax is a burden, as opposed to what pays

for road, hospitals, education and other infrastructures

of modern life (Lakoff, 2004).

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Frames

• Published road accident statistics record the conditions

of the driver as to alcohol or drug use but not the make

and year of the car or its safety features (Gusfield,

1981).

Gusfield, J. (1981). The Culture of Public Problems. Drinking-Driving and the Symbolic Order. The University of

Chicago Press.

Page 44: Andrea Saltelli

The issue of frames. How do we perceive the world. Socially constructed ignorance etc.

Lakoff, G., 2010, Why it Matters How We Frame the Environment, Environmental Communication: A Journal of Nature and Culture, 4:1, 70-81.

Lakoff, G., 2004-2014, Don’t think of an elephant: know your values and frame the debate, Chelsea Green Publishing.

For a summary see http://www.andreasaltelli.eu/file/repository/Hypocognition_Etc.pdf

Evidence based policy

George Lakoff

Page 45: Andrea Saltelli

Questions about GMO deemed relevant by citizens (Marris, 2001)

• Why do we need GMOs? What are the benefits?• Who will benefit from their use?• Who decided that they should be developed and how?• Why were we not better informed about their use in our

food, before their arrival on the market? • Why are we not given an effective choice about whether

or not to buy and consume these products?• Do regulatory authorities have sufficient powers and

resources to effectively counter-balance large companies who wish to develop these products?

Marris, C., Wynne, B., Simmons P., and Weldon, S. 2001. Final Report of the PABE research project funded by the Commission of EuropeanCommunities, Contract number: FAIR CT98-3844 (DG12 - SSMI), December 2001.

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Frames; GMO presented as a food scare.

“Montpelier is America’s only McDonald’s-free state capital. A fitting place, then, for a law designed to satisfy the unfounded fears of foodies […] genetically modified crops, declared safe by the scientific establishment, but reviled as Frankenfoods by the Subarus-and-sandals set”, (The Economist, 2014).

The Economist, Vermont v science, The little state that could kneecap the biotech industry, May 10th 2014

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Frames and narratives

For Akerlof and Shiller - against

what the ‘invisible hand’ would

contend - economic actors have no

choice but to exploit frames to

‘phish’ people into practices which

benefit the actors not the subject

phished.

George Akerlof

Robert R. Shiller

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On the persistence of narratives

“If is difficult to get a man to

understand something when his

salary depends upon his not

understanding it”

Upton Sinclair

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RULE SEVEN: Explore diligently the space of the

assumptions

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How to shake coupled ladders How coupled ladders are shaken

in most of available literature

RULE SEVEN: Explore diligently the space of the

assumptions

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END

Recent papers available at:

www.andreasaltelli.eu